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GPFS (General Parallel File System, brand name IBM Storage Scale and previously IBM Spectrum Scale) [1] is a high-performance clustered file system software developed by IBM. It can be deployed in shared-disk or shared-nothing distributed parallel modes, or a combination of these.
High-performance computing (HPC) as a term arose after the term "supercomputing". [3] HPC is sometimes used as a synonym for supercomputing; but, in other contexts, "supercomputer" is used to refer to a more powerful subset of "high-performance computers", and the term "supercomputing" becomes a subset of "high-performance computing".
Aerospike Database is a real-time, high performance NoSQL database. Designed for applications that cannot experience any downtime and require high read & write throughput. Aerospike is optimized to run on NVMe SSDs capable of efficiently storing large datasets (Gigabytes to Petabytes). Aerospike can also be deployed as a fully in-memory cache ...
More specifically, an SBA is a distributed-computing architecture for achieving linear scalability of stateful, high-performance applications using the tuple space paradigm. It follows many of the principles of representational state transfer (REST), service-oriented architecture (SOA) and event-driven architecture (EDA), as well as elements of ...
Even though it is very difficult to further speed up a single thread or single program, most computer systems are actually multitasking among multiple threads or programs. Thus, techniques that improve the throughput of all tasks result in overall performance gains. Two major techniques for throughput computing are multithreading and ...
Memory hierarchy affects performance in computer architectural design, algorithm predictions, and lower level programming constructs involving locality of reference. Designing for high performance requires considering the restrictions of the memory hierarchy, i.e. the size and capabilities of each component.
While early supercomputers used a few fast, closely packed processors that took advantage of local parallelism (e.g., pipelining and vector processing), in time the number of processors grew, and computing nodes could be placed further away, e.g., in a computer cluster, or could be geographically dispersed in grid computing.
The High Performance Conjugate Gradients Benchmark (HPCG benchmark) is a supercomputing benchmark test proposed by Michael Heroux from Sandia National Laboratories, and Jack Dongarra and Piotr Luszczek from the University of Tennessee.